Gender recognition from unconstrained selfie images: a convolutional neural network approach

<p>Human gender recognition is an essential demographic tool. This is reflected in forensic science, surveillance systems and targeted marketing applications. This research was always driven using standard face images and hand-crafted features. Such way has achieved good results, however, the reliability of the facial images had a great effect on the robustness of extracted features, where any small change in the query facial image could change the results. Nevertheless, the performance of current techniques in unconstrained environments is still inefficient, especially when contrasted against recent breakthroughs in different computer vision research. This paper introduces a novel technique for human gender recognition from non-standard selfie images using deep learning approaches. Selfie photos are uncontrolled partial or full-frontal body images that are usually taken by people themselves in real-life environment. As far as we know this is the first paper of its kind to identify gender from selfie photos, using deep learning approach. The experimental results on the selfie dataset emphasizes the proposed technique effectiveness in recognizing gender from such images with 89% accuracy. The performance is further consolidated by testing on numerous benchmark datasets that are widely used in the field, namely: Adience, LFW, FERET, NIVE, Caltech WebFaces and<br />CAS-PEAL-R1.</p>

Novel Application of a Force Sensor during Sit-to-Stands to Measure Dynamic Cerebral Autoregulation Onset

Purpose: Current sit-to-stand methods measuring dynamic cerebral autoregulation (dCA) do not capture the precise onset of the time delay (TD) response. Reduced sit-to-stand reactions in older adults and individuals post-stroke could inadvertently introduce variability, error, and imprecise timing. We applied a force sensor during a sit-to-stand task to more accurately determine how TD before dCA onset may be altered. Methods: Middle cerebral artery blood velocity (MCAv) and mean arterial pressure (MAP) were measured during two sit-to-stands separated by 15 minutes. Recordings started with participants sitting on a force-sensitive resistor for 60 seconds, then asked to stand for two minutes. Upon standing, the force sensor voltage immediately dropped and marked the exact moment of arise-and-off (AO). Time from AO until an increase in cerebrovascular conductance (CVC = MCAv/MAP) was calculated as TD. Results: We tested the sensor in 4 healthy young adults, 2 older adults, and 2 individuals post-stroke. Healthy young adults stood quickly and the force sensor detected a small change in TD compared to classically estimated AO, from verbal command to stand. When compared to the estimated AO, older adults had a delayed measured AO and TD decreased up to ~50% while individuals post-stroke had an early AO and TD increased up to ~14%. Conclusion: The transition reaction speed during the sit to stand has the potential to influence dCA metrics. As observed in the older adults and participants with stroke, this response may drastically vary and influence TD.

Semi-Adaptive Evolution with Spontaneous Modularity of Half-Chaotic Randomly Growing Autonomous and Open Networks

Up until now, studies of Kauffman network stability have focused on the conditions resulting from the structure of the network. Negative feedbacks have been modeled as ice (nodes that do not change their state) in an ordered phase but this blocks the possibility of breaking out of the range of correct operation. This first, very simplified approximation leads to some incorrect conclusions, e.g., that life is on the edge of chaos. We develop a second approximation, which discovers half-chaos and shows its properties. In previous works, half-chaos has been confirmed in autonomous networks, but only using node function disturbance, which does not change the network structure. Now we examine half-chaos during network growth by adding and removing nodes as a disturbance in autonomous and open networks. In such evolutions controlled by a ‘small change’ of functioning after disturbance, the half-chaos is kept but spontaneous modularity emerges and blurs the picture. Half-chaos is a state to be expected in most of the real systems studied, therefore the determinants of the variability that maintains the half-chaos are particularly important in the application of complex network knowledge.

A Simple Model to Compute the Characteristic Parameters of a Slotted Rectangular Microstrip Patch Antenna

In this study, we developed an analytical model of slot-loaded rectangular microstrip patch antennas based on the simulation results by varying slot parameters. The dominant resonant frequency predicted by such a model is in strong agreement with the experimental results measured at several locations of slot-loaded rectangular microstrip patch antennas. The model enables a reliable and quick computation of the resonant frequency, which generally follows a harmonic behavior that nearly resembles the resonant frequency of a microstrip antenna without a slot, which can be related to a small change in the impedance caused by the slot position. Results showed a good agreement between simulations and measurements for all the slot positions. Mathematical analytic functions to describe the changes in specific characteristic parameters of the slot-loaded rectangular microstrip patch antennas are also included.

Fast 3D Content Update for Wide-Angle Holographic Near-Eye Display

Near-eye holographic displays are the holy grail of wear-on 3D display devices because they are intended to project realistic wide-angle virtual scenes with parameters matching human vision. One of the key features of a realistic perspective is the ability to move freely around the virtual scene. This can be achieved by addressing the display with wide-angle computer-generated holograms (CGHs) that enable continuous viewpoint change. However, to the best of our knowledge there is no technique able to generate these types of content. Thus, in this work we propose an accurate and non-paraxial hologram update method for wide-angle CGHs that supports continuous viewpoint change around the scene. This method is based on the assumption that with a small change in perspective, two consecutive holograms share overlapping data. This enables reusing the corresponding part of the information from the previous view, eliminating the need to generate an entirely new hologram. Holographic information for the next viewpoint is calculated in two steps: first, a tool approximating the Angular Spectrum Propagation is proposed to generate the hologram data from previous viewpoint; and second, the efficient Phase Added Stereogram algorithm is utilized for generating the missing hologram content. This methodology offers fast and accurate calculations at the same time. Numerical and optical experiments are carried out to support the results of the proposed method.

Simulation of Stress Concentrations in Notches

The fatigue life curves of materials are very sensitive to the magnitude of the stress amplitude. A small change or inaccuracy in the determination of the stress value causes large changes or inaccuracies in the calculated fatigue life estimate. Therefore, the use of computer simulations for fatigue life estimation requires a proper model development methodology. The paper is devoted to the problem of the modeling of components in notches using FEM. The modeling parameters significantly influencing the obtained stress results have been defined. Exact analytical solutions served as a benchmark for comparing the accuracy of the stress values obtained using FEM models. For the selected 2D and 3D notched components, diagrams were created for sensitivity analysis of the influence of the mesh element density at the root of the notch in correlation with the exact analytical solution. The findings from model building were applied to model the stress concentration at the root of a V-weld joint in a gas pipeline.

Economy and supply

A review of the contribution that the study of London makes to our understanding of the ancient economy. It explores the economic impact of the large-scale movement of goods and supplies required to support military advance, and to meet the expectations of the unusually large garrison stationed in Britain. The underwriting of these food supplies can be treated as an early form of military annona, sharing characteristics with arrangements made for the feeding of larger cities. It is argued that London’s economy and port, revolved around the needs of annona supply embracing military and civilian consumers. The infrastructure developed to support the annona stimulated a wider trade in luxury imports, best evidenced by the pottery carried to and through London (such as Samian and amphorae). This long-distance supply is the most archaeologically evident aspect of London’s Roman economy. The use of coin is another, and this chapter reviews the use of small change within London’s internal economy and local taxes. Coin-based market economies may not have penetrated far into the surrounding countryside, where subsistence and peasant farming was allowed to persist and rent and tax could be obtained through sharecropping and other ‘in kind’ arrangements.